Removing Duplicate Rows in Oracle SQL Using Aggregation and Ranking Functions

Removing Duplicates on Specific Rows in Oracle Query

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Removing duplicate rows from a database table is a common requirement in data analysis and reporting. In this article, we will discuss how to remove duplicates based on specific column values using Oracle SQL.

Understanding the Problem

The problem statement involves removing duplicate rows from an Oracle database table myTable where the combination of values in columns col1, col2, and col3 results in multiple rows with the same value for column col4. We want to keep only one row with the minimum value of col5 for each combination of col1, col2, and col3.

Current Oracle Query

The current query provided is:

SELECT col1, col2, col3, col4
FROM myTable
WHERE myConditions
ORDER BY col5;

This query filters the table based on conditions in column myConditions and orders the results by column col5. However, this approach does not address the issue of duplicate rows for specific combinations of columns.

Solution Overview

To solve this problem, we will use a combination of aggregation and ranking functions provided by Oracle SQL. We will group the table by the specified columns (col1, col2, and col3) and use the KEEP clause with DENSE_RANK to select only the row with the minimum value for column col5.

Solution Implementation

We can implement the solution using the following Oracle query:

SELECT col1, col2, col3, MIN(col4) KEEP (DENSE_RANK FIRST ORDER BY col5)
FROM myTable
WHERE myConditions
GROUP BY col1, col2, col3
ORDER BY col1, col2, col3;

Here’s a breakdown of the query:

SELECT col1, col2, col3, MIN(col4): We select only the specified columns (col1, col2, and col3) and use the minimum value for column col4.
KEEP (DENSE_RANK FIRST ORDER BY col5): This clause is used to rank the rows based on the value of column col5. The DENSE_RANK function assigns a unique rank to each row without gaps. We specify FIRST to keep only the first-ranked row.
FROM myTable WHERE myConditions: We filter the table based on conditions in column myConditions.
GROUP BY col1, col2, col3: We group the table by the specified columns (col1, col2, and col3).
ORDER BY col1, col2, col3: Finally, we order the results by the grouped columns.

How it Works

Here’s a step-by-step explanation of how the query works:

The query groups the table by the specified columns (col1, col2, and col3).
For each group, the query calculates the minimum value for column col4.
The KEEP (DENSE_RANK FIRST ORDER BY col5) clause assigns a unique rank to each row within each group based on the value of column col5. Since we specify FIRST, only the first-ranked row is kept.
Finally, the query orders the results by the grouped columns.

Example Output

The output of this query would be:

COL1 COL2 COL3 COL4
A    A     1     3
A    B     1     0
A    B     2     4

As shown in the example output, only one row with a unique combination of col1, col2, and col3 values is kept. The value for column col4 is also minimized.

Conclusion

In this article, we discussed how to remove duplicate rows based on specific column values using Oracle SQL. We implemented a solution using the KEEP clause with DENSE_RANK to select only the row with the minimum value for column col5. The provided example demonstrates how to apply this solution to a real-world scenario.

Additional Tips and Variations

In addition to removing duplicates, you can use aggregate functions like MIN, MAX, or AVG to calculate values based on specific columns.
To handle ties in column col5, you can modify the query to use a different ranking function, such as RANK or DENSE_RANK.
Make sure to adjust the grouping clause according to your requirements.

References

For more information on Oracle SQL features and functions, please refer to the official Oracle documentation:

https://docs.oracle.com/en/database/oracle/oracle-database/21/sql/sql-junctions.html

By using this query, you can efficiently remove duplicate rows based on specific column values in your Oracle database.

Last modified on 2024-05-29